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--- disaggregation_of_crop_areas [2020/03/28 09:01] – [Data sets] matsz
+++ disaggregation_of_crop_areas [2022/11/07 10:23] (current) – external edit 127.0.0.1
@@ Line 15: / Line 15: @@
 Primacy of land stability means that if there is no indication (i. e. new observation, policy restricting previous land distributions, …) it is more likely that the spatial pattern remains similar to the previous (prior) pattern. Therefore, once a likely distribution of land and livestock has been determined on the basis of high-resolution FSS statistics, the model tries to stay as close as possible to this distribution. This is achieved with penalty factors that are activated as soon as the estimated land use area deviated from the prior values, assigning a higher penalty for deviations of permanent crops and forests, and very high penalties of a land use is estimated in a spatial unit where it didn’t exist in the prior’s data base.
-The disaggregation model m_hpdCropSpat is described in Section 7.4.1. FIXME Section 7.4.2 describes the required input data, and Section 7.4.3 describes the preparation of the input data for their use in hpdCropSpat.
+The disaggregation model m_hpdCropSpat is described in [[disaggregation_of_crop_areas#simulation_model_m_hpdcropspat|Section Simulation model m_hpdCropSpat]].[[disaggregation_of_crop_areas#data_sets|Section Data sets]] describes the required input data, and [[disaggregation_of_crop_areas#data_preparation|Section Data preparation]] describes the preparation of the input data for their use in hpdCropSpat.
 ====Simulation model m_hpdCropSpat====
@@ Line 32: / Line 32: @@
 \end{equation}
-\(a_{c^*,h}\) =	Area [parameter, km2] cultivated with crop c or covered by ‘other land’ use excluding forest in spatial unit h \\
+\(a_{c^*,h}\) =	Area [parameter, km<sup>2</sup>] cultivated with crop //c// or covered by ‘other land’ use excluding forest in spatial unit //h// \\
-\(A_{c^*,h}\) =	Area [parameter, km2] cultivated with crop c or covered by ‘other land’ use excluding forest in region r
+\(A_{c^*,h}\) =	Area [parameter, km<sup>2</sup>] cultivated with crop //c// or covered by ‘other land’ use excluding forest in region //r//
 ===Equation 2 ADDUPGRID_===
@@ Line 55: / Line 55: @@
 \end{equation}
-\(a_h\)	= Area [parameter, km2] of spatial unit h
+\(a_h\)	= Area [parameter, km<sup>2</sup>] of spatial unit// h//  \\
-\(a_{c^*,h}\)	 =Area [parameter, km2] cultivated with crop c or covered by ‘other land’ use excluding forest in spatial unit h
+\(a_{c^*,h}\)	 =Area [parameter, km<sup>2</sup>] cultivated with crop// c// or covered by ‘other land’ use excluding forest in spatial unit //h// \\
 \(\epsilon_{a,h}\) =	Error term, allowing a spatial unit to shrink or grow slightly in order to enable a feasible disaggregation of statistical data.
@@ Line 256: / Line 256: @@
 \end{equation}
-\(a_{hg}\) =	Area [parameter, km2] of unit //u// intersecting spatial unit //h// and grid cell //g//. \\
+\(a_{hg}\) =	Area [parameter, km<sup>2</sup>] of unit //u// intersecting spatial unit //h// and grid cell //g//. \\
-\(a_h\)	= Area [parameter, km2] of spatial unit //h// \\
+\(a_h\)	= Area [parameter, km<sup>2</sup>] of spatial unit //h// \\
 \(f_{hg}\) =	Fraction of spatial unit// h//, which is covered by grid cell //g// \\
@@ Line 268: / Line 268: @@
 \end{equation}
-\(c^*\)	Land use. c^*∈{c,other land} \\
+\(c^*\)	= Land use. \(c^*\in\{c,other \; land\}\) \\
-\(a_{c^o,hg}\)		Area [parameter, km<sup>2</sup>] cultivated with crop //c// or covered by ‘other land’ use excluding forest in unit //u// intersecting spatial unit //h// and grid cell //g//.  \\
+\(a_{c^o,hg}\)		= Area [parameter, km<sup>2</sup>] cultivated with crop //c// or covered by ‘other land’ use excluding forest in unit //u// intersecting spatial unit //h// and grid cell //g//.  \\
-\(a_{c^o,h}\)		Area [parameter, km<sup>2</sup>] cultivated with crop //c// or covered by ‘other land’ use excluding forest in spatial unit //h// \\
+\(a_{c^o,h}\)		= Area [parameter, km<sup>2</sup>] cultivated with crop //c// or covered by ‘other land’ use excluding forest in spatial unit //h// \\
-\(f_{hg}\)		Fraction of spatial unit //h//, which is covered by grid cell //g// \\
+\(f_{hg}\)		= Fraction of spatial unit //h//, which is covered by grid cell //g// \\
+Note that this re-mapping is done in each step, however it affects only the step ‘A priori land use distribution’ which is constrained by data for the intersections of the FSS-10km grid cells with NUTS3 regions. These units are not aligned with the spatial units (HSU) for two reasons:
+  - HSU are aligned with a regular grid of 0.25° x 0.25° but not to a grid of 10 km x 10 km
+  - Even though HSU are aligned with a NUTS3 administrative region layer, changes in the definition of NUTS3 regions over time create shifts in the boundaries
+In all other steps, the constraining data set is taken from CAPRI NUTS2 regions to which all spatial units are nested to and \(f_{hr}=1\forall h,r\).
+The same holds if disaggregation is done into the FSU units, which are part of exactly one FSS grid cell.
+//Dealing with FSS grid cells with too much crops//
+  Line 613ff
+  p_temp3dim(%region%,"AREA","<0")$(p_nutslevl(%region%,"AREA") and (p_nutslevl(%region%,"OTHER")<0))
+	=(p_nutslevl(%region%,"CROPS")+p_nutslevl(%region%,"FORE"))/p_nutslevl(%region%,"AREA");
+  p_nutslevl(%region%,"AREAcorr")=p_temp3dim(%region%,"AREA","<0");
+  # Rescale total and crop area of units if the total area in the %region% had to be changed.
+  p_levlunit(%region%,cur%spatunit%,"AREA")$(p_temp3dim(%region%,"AREA","<0"))
+	=p_levlunit(%region%,cur%spatunit%,"AREA")*p_temp3dim(%region%,"AREA","<0");
+  p_levlunit(%region%,cur%spatunit%,"OTHER")$(not p_temp3dim(%region%,"AREA","<0"))
+	=max(0,p_levlunit(%region%,cur%spatunit%,"AREA")-
+			sum(%croptp%,p_levlunit(%region%,cur%spatunit%,%croptp%)));
+Farm structure surveys collect data on crop areas and allocate them to the geographic location where the farmer resides. Therefore, it is not excluded that a spatial unit (grid cell) has more crop area than the cell is large. It is not possible to ‘correct’ those allocations.
+CAPRI works with an area-consistent approach, thus the total area available must be exactly matching the sum of the areas used for different purposes. As a re-allocation of ‘surplus’ crop areas is not possible, we inflate the area of spatial units h so that all forest and crop areas can be accommodated. The area of ‘other’ land uses is adapted to ensure coherence.
+\begin{equation}
+a_{hg} \leftarrow a_{hg} \cdot \frac{a_{g,forest} + \sum_c a_{g,c}}{a_g}
+\end{equation}
+\begin{equation}
+a_{hg, other} = a_{hg} - a_{hg,forest} - \sum_c a_{hg,c}
+\end{equation}
+Note that this ‘manipulation’ of the data is needed to avoid any potential infeasibilities in the land use disaggregation model maintaining the relevant information from the different data sets:
+  * The total crop areas data collected in the FSS
+  * The heterogeneity of crop areas (‘suitability’) as modelled with the LAPModel. This concerns both the spatial heterogeneity within a region across spatial units, as well as the relative abundance of different crops in a single spatial unit.
+===Adding previously unobserved crops===
+It might well be that crops occur in a grid cell or region which were not predicted or which had not been observed ‘before’ (e.g. when moving from ex-post to ex-ante simulation). In this case prior estimates of the distribution need to be developed.
+This is done on the basis of ‘similarity’ assuming that similar crops have similar preferences for natural conditions (or available infrastructure) and a similar spatial heterogeneity.
+This ‘gap-filling’ is done in three hierarchical steps:
+. Average crop area of similar crops in the same spatial unit as defined in the set mactgroups:
+  set mactgroups(sgroups,*) "Groups with similar crops - LAPM activities" /
+    CERE.(BARL,SWHE,DWHE,LMAIZ,OATS,RYEM,OCER,PARI)
+    VEGE.(TOMA,OVEG,SUGB,POTA,PULS,FLOW)
+    FODD.(ROOF,OFAR,LGRAS)
+    OILS.(SOYA,LRAPE,SUNF)
+    FORE.(FORE)
+    TREE.(APPL,CITR,OFRU,NURS,NUTS,LOLIV,LVINY)/;
+. If there are no ‘similar’ crops in the region or grid cell, the average area of all available crops is used. \\
+. If there is still no prediction of the in the spatial unit, the same crop area is given to the prior estimates in all spatial units in the region/grid cell.
+===Checking availability of standard deviations===
+**May become obsolete for the CAPDIS modules of the CAPRI stable release versions following STAR 2.4**
+The LAPModel provides not only prediction for crop shares for each HSU, but at the same time also an estimate for the standard deviation of each estimate. These standard deviations are ‘carried’ on throughout the CAPRI disaggregation steps.
+The procedures described above however made evident that some crops might appear in spatial units where they have not been observed before; obviously, an estimate of the standard deviation must be provided as well.
+If the crops have been observed in other spatial units of the region or grid, the maximum relative standard deviation is used. If the crop has not been observed in the whole region or grid, the maximum standard deviation over all observed crops is used.  Still missing standard deviations are assumed to be 100%.
+Standard deviation for ‘other land uses’ are also set to a default of 100%, but can be modified by the user (through the CAPRI GUI).
+===Preparation for specific applications===
+  Lines 690ff
+  p_temp3dim(%region%,"loshare",%croptp%)$ p_nutslevl(%region%,%croptp%)
+	= max(disagg("mincropshare"),p_temp3dim(%region%,"share",%croptp%)*disagg("relcropshare"));
+  p_levlunit(%region%,cur%spatunit%,%croptp%)
+  $((p_levlunit(%region%,cur%spatunit%,%croptp%)/sum(%croptp%1,p_levlunit(%region%,cur%spatunit%,%croptp%1))
+  <p_temp3dim(%region%,"loshare",%croptp%)) and not (sameas(%croptp%,"other")))
+	=0;
+For some applications, the focus is on the analysis of dominant crops in each spatial unit, for example, when linking the result of the disaggregation with process-based crop models. This is done on the basis of two parameters:
+\begin{equation}
+a_{hc}= 0 \leftarrow \frac {a_{h,c}} {\sum_{c^{\prime}}a_{h,c^\prime}} \lt max⁡ \left[ χ_{min},\frac{a_{r,c}}{\sum_{c^\prime}a_{r,c^\prime} } \cdot χ_{rel} \right]
+\end{equation}
+\(χ_{min}\) = Minimum crop share allowed in the spatial unit \\
+\(χ_{rel}\) = Minimum relative crop share – defines heterogeneity of crop shares for a crop in a spatial unit