te_schemas.reporting

class te_schemas.reporting.AffectedPopulationReport

AffectedPopulationReport(summary: Dict[str, te_schemas.reporting.PopulationList])

__init__(summary)
Parameters:

summary (Dict[str, PopulationList])

Return type:

None

summary: Dict[str, PopulationList]
class te_schemas.reporting.Area

Area(name: Optional[str], area: float)

__init__(name, area)
Parameters:

  • name (str | None)

  • area (float)

Return type:

None

area: float
name: str | None
class te_schemas.reporting.AreaList

AreaList(name: Optional[str], unit: str, areas: List[te_schemas.reporting.Area])

__init__(name, unit, areas)
Parameters:

  • name (str | None)

  • unit (str)

  • areas (List[Area])

Return type:

None

areas: List[Area]
name: str | None
unit: str
class te_schemas.reporting.CounterbalancingLandTypeResult

Gains, losses, and delta LDN for a single land type.

__init__(land_type_name, gains_area_sq_km, losses_area_sq_km, delta_ldn, ldn_achieved)
Parameters:

  • land_type_name (str)

  • gains_area_sq_km (float)

  • losses_area_sq_km (float)

  • delta_ldn (float)

  • ldn_achieved (bool)

Return type:

None

delta_ldn: float
gains_area_sq_km: float
land_type_name: str
ldn_achieved: bool
losses_area_sq_km: float
class te_schemas.reporting.CounterbalancingReport

Full counterbalancing report for one assessment period.

__init__(land_type_results, overall_ldn_achieved)
Parameters:
Return type:

None

land_type_results: List[CounterbalancingLandTypeResult]
overall_ldn_achieved: bool
class te_schemas.reporting.CrossTab

A cross-tabulation of land area by two classification layers.

Used to summarise how land area is distributed across combinations of an initial-period classification (rows) and a final-period classification (columns).

__init__(name, unit, initial_year, final_year, values)
Parameters:

  • name (str | None)

  • unit (str)

  • initial_year (int)

  • final_year (int)

  • values (List[CrossTabEntry])

Return type:

None

final_year: int

End year of the final (reporting) period.

initial_year: int

Start year of the initial (baseline) period.

name: str | None
unit: str
values: List[CrossTabEntry]

List of cross-tabulation entries, one per (row, column) cell.

class te_schemas.reporting.CrossTabEntry

A single cell in a cross-tabulation matrix.

Each entry represents the area (or other metric) for a specific combination of initial and final classification labels.

__init__(initial_label, final_label, value)
Parameters:

  • initial_label (str)

  • final_label (str)

  • value (float)

Return type:

None

final_label: str

Classification label for the final period (columns of the matrix).

initial_label: str

Classification label for the initial period (rows of the matrix).

value: float

Area or metric value for this (initial_label, final_label) combination.

class te_schemas.reporting.CrossTabEntryInitialFinal

CrossTabEntryInitialFinal(initial_label: str, final_label: str, initial_value: float, final_value: float)

__init__(initial_label, final_label, initial_value, final_value)
Parameters:

  • initial_label (str)

  • final_label (str)

  • initial_value (float)

  • final_value (float)

Return type:

None

final_label: str
final_value: float
initial_label: str
initial_value: float
class te_schemas.reporting.CrossTabInitialFinal

CrossTabInitialFinal(name: Optional[str], unit: str, initial_year: int, final_year: int, values: List[te_schemas.reporting.CrossTabEntryInitialFinal])

__init__(name, unit, initial_year, final_year, values)
Parameters:
Return type:

None

final_year: int
initial_year: int
name: str | None
unit: str
values: List[CrossTabEntryInitialFinal]
class te_schemas.reporting.DroughtExposedPopulation

DroughtExposedPopulation(drought_class: str, year: int, exposed_population: List[te_schemas.reporting.Population])

__init__(drought_class, year, exposed_population)
Parameters:

  • drought_class (str)

  • year (int)

  • exposed_population (List[Population])

Return type:

None

drought_class: str
exposed_population: List[Population]
year: int
class te_schemas.reporting.DroughtReport

DroughtReport(tier_one: Dict[int, te_schemas.reporting.AreaList], tier_two: Dict[int, Dict[str, te_schemas.reporting.PopulationList]], tier_three: Dict[int, te_schemas.reporting.Value])

__init__(tier_one, tier_two, tier_three)
Parameters:
Return type:

None

tier_one: Dict[int, AreaList]
tier_three: Dict[int, Value]
tier_two: Dict[int, Dict[str, PopulationList]]
class te_schemas.reporting.ErrorClassificationProperties

ErrorClassificationProperties(area: float, type: str, place_name: str, process: str, basis: str, periods: str)

__init__(area, type, place_name, process, basis, periods)
Parameters:

  • area (float)

  • type (str)

  • place_name (str)

  • process (str)

  • basis (str)

  • periods (str)

Return type:

None

area: float
basis: str
periods: str
place_name: str
process: str
type: str
class te_schemas.reporting.HotspotBrightspotProperties

HotspotBrightspotProperties(name: str, area: float, type: str, process: str, basis: str, periods: List[str])

__init__(name, area, type, process, basis, periods)
Parameters:

  • name (str)

  • area (float)

  • type (str)

  • process (str)

  • basis (str)

  • periods (List[str])

Return type:

None

area: float
basis: str
name: str
periods: List[str]
process: str
type: str
class te_schemas.reporting.LandConditionAssessment

Report on land condition within a particular period.

__init__(sdg, productivity, land_cover, soil_organic_carbon, error_recode=None, sdg_error_recode=None)
Parameters:
Return type:

None

error_recode: ErrorRecodePolygons | None = None

Polygons indicating false positives and false negatives in the SDG Indicator 15.3.1 layer.

land_cover: LandCoverReport

Report on land cover.

productivity: ProductivityReport

Report on land productivity.

sdg: SDG15Report

Summary statistics on SDG Indicator 15.3.1.

sdg_error_recode: AreaList | None = None

Summary statistics on false positive/negative areas.

soil_organic_carbon: SoilOrganicCarbonReport

Report on soil organic carbon.

class te_schemas.reporting.LandConditionChange

Cross-tabulation of baseline vs reporting-period assessment.

Each field is a cross-tabulation whose rows represent the baseline-period indicator assessment (Improved / Stable / Degraded) and whose columns represent the reporting-period indicator assessment (Improved / Stable / Degraded). Cell values are land areas. No data may also be included as a category.

__init__(sdg, productivity, land_cover, soil_organic_carbon)
Parameters:
Return type:

None

land_cover: CrossTab

Baseline vs reporting-period assessment for land cover.

productivity: CrossTab

Baseline vs reporting-period assessment for land productivity.

sdg: CrossTab

Baseline vs reporting-period assessment for the combined SDG 15.3.1 indicator (one-out, all-out rule across productivity, land cover, and soil organic carbon).

soil_organic_carbon: CrossTab

Baseline vs reporting-period assessment for soil organic carbon.

class te_schemas.reporting.LandConditionReport

Full land-condition report for one reporting period.

Combines three complementary views of land condition:

  • period_assessment – per-period indicator values and summaries (improved / stable / degraded areas for each sub-indicator).

  • status_assessment – final degradation status after applying the 3×3 reclassification rule to derive status from baseline and reporting-period assessments.

  • change_assessment – 3×3 cross-tabulations of baseline assessment (rows) vs reporting-period assessment (columns) for each sub-indicator. These are the raw inputs to the status rule.

__init__(period_assessment, status_assessment=None, change_assessment=None)
Parameters:
Return type:

None

change_assessment: LandConditionChange | None = None

Cross-tabulations of baseline vs reporting-period assessment (one per sub-indicator). These are the inputs used to derive status_assessment.

period_assessment: LandConditionAssessment

Indicator-level assessment for this period (areas by class for SDG, productivity, land cover, and soil organic carbon).

status_assessment: LandConditionStatus | None = None

Degradation status derived by applying the UNCCD 3×3 reclassification rule to baseline and reporting-period assessments.

class te_schemas.reporting.LandConditionStatus

Report on land condition for a particular period, relative to baseline.

__init__(sdg, productivity, land_cover, soil_organic_carbon)
Parameters:
Return type:

None

land_cover: AreaList

Report on land cover.

productivity: Dict[str, AreaList]

Report on land productivity.

sdg: AreaList

Summary statistics on SDG Indicator 15.3.1.

soil_organic_carbon: Dict[str, AreaList]

Report on soil organic carbon.

class te_schemas.reporting.LandCoverReport

Report on land cover within a particular period.

__init__(summary, legend_nesting, transition_matrix, crosstabs_by_land_cover_class, land_cover_areas_by_year)
Parameters:
Return type:

None

crosstabs_by_land_cover_class: List[CrossTab]
land_cover_areas_by_year: ValuesByYearDict
legend_nesting: LCLegendNesting
summary: AreaList
transition_matrix: LCTransitionDefinitionDeg
class te_schemas.reporting.Population

Population(name: Optional[str], population: int, type: str)

__init__(name, population, type)
Parameters:

  • name (str | None)

  • population (int)

  • type (str)

Return type:

None

name: str | None
population: int
type: str
class te_schemas.reporting.PopulationList

PopulationList(name: Optional[str], values: List[te_schemas.reporting.Population])

__init__(name, values)
Parameters:
Return type:

None

name: str | None
values: List[Population]
class te_schemas.reporting.ProductivityReport

Report on land productivity within a particular period.

__init__(summaries, crosstabs_by_productivity_class)
Parameters:

  • summaries (Dict[str, AreaList])

  • crosstabs_by_productivity_class (List[CrossTab])

Return type:

None

crosstabs_by_productivity_class: List[CrossTab]
summaries: Dict[str, AreaList]
class te_schemas.reporting.ReportMetadata

ReportMetadata(title: str, date: datetime.datetime, trends_earth_version: te_schemas.schemas.TrendsEarthVersion, area_of_interest: te_schemas.schemas.AreaOfInterest, affected_areas_only: bool = False)

class Meta
datetimeformat = '%Y-%m-%dT%H:%M:%S+00:00'
__init__(title, date, trends_earth_version, area_of_interest, affected_areas_only=False)
Parameters:
Return type:

None

affected_areas_only: bool = False
area_of_interest: AreaOfInterest
date: datetime
title: str
trends_earth_version: TrendsEarthVersion
class te_schemas.reporting.SDG15Report

Summary report on SDG Indicator 15.3.1.

__init__(summary)
Parameters:

summary (AreaList)

Return type:

None

summary: AreaList
class te_schemas.reporting.SoilOrganicCarbonReport

Report on soil organic carbon within a particular period.

__init__(summaries, soc_stock_by_year)
Parameters:
Return type:

None

soc_stock_by_year: ValuesByYearDict

Soil organic carbon stock by year and land cover class

summaries: Dict[str, AreaList]

Summary statistics on change in soil organic carbon, stored as a dict, where keys indicate summary type (over “all_cover_types” or “non_water”), and values indicate areas improved, stable, degraded, or no data.

class te_schemas.reporting.TrendsEarthCounterbalancingSummary

TrendsEarthCounterbalancingSummary(metadata: te_schemas.reporting.ReportMetadata, counterbalancing: te_schemas.reporting.CounterbalancingReport)

__init__(metadata, counterbalancing)
Parameters:
Return type:

None

counterbalancing: CounterbalancingReport
metadata: ReportMetadata
class te_schemas.reporting.TrendsEarthDroughtSummary

TrendsEarthDroughtSummary(metadata: te_schemas.reporting.ReportMetadata, drought: te_schemas.reporting.DroughtReport)

__init__(metadata, drought)
Parameters:
Return type:

None

drought: DroughtReport
metadata: ReportMetadata
class te_schemas.reporting.TrendsEarthLandConditionSummary

TrendsEarthLandConditionSummary(metadata: te_schemas.reporting.ReportMetadata, land_condition: Dict[str, te_schemas.reporting.LandConditionReport], affected_population: Dict[str, te_schemas.reporting.AffectedPopulationReport])

__init__(metadata, land_condition, affected_population)
Parameters:
Return type:

None

affected_population: Dict[str, AffectedPopulationReport]
land_condition: Dict[str, LandConditionReport]
metadata: ReportMetadata
class te_schemas.reporting.Value

Value(name: str, value: float)

__init__(name, value)
Parameters:

  • name (str)

  • value (float)

Return type:

None

name: str
value: float
class te_schemas.reporting.ValuesByYearDict

ValuesByYearDict(name: str, unit: str, values: Dict[int, Dict[str, float]])

__init__(name, unit, values)
Parameters:

  • name (str)

  • unit (str)

  • values (Dict[int, Dict[str, float]])

Return type:

None

name: str
unit: str
values: Dict[int, Dict[str, float]]